
> ## ---- Setup ----
> ## lmer estimation algorithm control
> strict_tol <- lmerControl(optCtrl = list(xtol_abs = 1e-8,
+                                          ftol_abs = 1e-8))

> ## ---- Data ----
> load("dat/proc-data/soep_imp.RData")

> soep_desc <- soep_imp$imputations$imp1 %>%
+   filter(year == 2018) %>%
+   dplyr::select(id, year, vote2017, vote_afd, cmr_arm, owner, weight) %>%
+   dplyr::mutate(owner = factor(owner, levels = , c(0, 1), labels = c("Renters", "Owners"))) %>%
+   dplyr::rename(
+     Ownership = owner,
+     `Voted AfD in 2017` = vote_afd,
+     `Market Rents (EUR/sqm)` = `cmr_arm`
+   ) %>%
+   na.omit()

> ## ---- Rent plots ---
> parties <- "AfD"

> rent_vars <- "Market Rents (EUR/sqm)"

> group_vars <- "Ownership"

> for (party in parties) {
+   for (rent_var in rent_vars) {
+     for (group in group_vars) {
+       x_range <- soep_desc %>% 
+         filter(vote2017 != "None") %>%
+         dplyr::select(all_of(rent_var)) %>% 
+         range()
+       
+       num_groups <- soep_desc %>%
+         filter(vote2017 != "None") %>%
+         dplyr::select(all_of(group)) %>% 
+         table() %>%
+         length()
+         
+       
+       plot_temp <- ggrent_plot(
+         dat = soep_desc %>% 
+           filter(vote2017 != "None") %>%
+           mutate(!!paste0("Voted for ", party, " in 2017") := as.numeric(vote2017 == party)),
+         x = rent_var,
+         y = paste0("Voted for ", party, " in 2017"),
+         group = group,
+         weight = "weight",
+         num_splines = 1L,
+         heights = c(4, 2),
+         xlim = x_range,
+         font_size = 18L
+       )
+       
+       ggsave(
+         filename = make.names(paste0("ggrent_plot_", party, "_", rent_var, "_", group, ".pdf")),
+         plot = plot_temp,
+         path = "fig",
+         width = 6 * num_groups,
+         height = 9,
+         dpi = 300,
+         limitsize = FALSE
+       )
+     }
+   }
+ }
